Update app.py

app.py

@@ -1,19 +1,26 @@
 from langchain.prompts.prompt import PromptTemplate
 from langchain.llms import OpenAI
 from langchain.chains import ChatVectorDBChain
+from langchain.embeddings import HuggingFaceEmbeddings
 import os
+import FAISS
 from typing import Optional, Tuple
 import gradio as gr
 import pickle
 from threading import Lock
 
-with open("vanguard_vectorstore.pkl", "rb") as f:
-    vectorstore = pickle.load(f)
+model_sbert = "sentence-transformers/all-mpnet-base-v2"
 
-print(vectorstore)
-query = 'What is the benefit of investing in an ETF?'
 
-print(vectorstore.similarity_search(query,2))
+sbert_emb = HuggingFaceEmbeddings(model_name=model_sbert)
+
+def load_vectorstore(folder,embeddings):
+    
+    vectorstore = FAISS.load_local(folder,embeddings) 
+
+    return vectorstore
+
+vectorstore = load_vectorstore('vanguard-embeddings',sbert_emb)
     
 _template = """Given the following conversation and a follow up question, rephrase the follow up question to be a standalone question.
 You can assume the question about investing and the investment management industry.